Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parall...Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.展开更多
Brain-Computer interfacing(BCI)has currently added a new dimension in assistive robotics.Existing braincomputer interfaces designed for position control applications suffer from two fundamental limitations.First,most ...Brain-Computer interfacing(BCI)has currently added a new dimension in assistive robotics.Existing braincomputer interfaces designed for position control applications suffer from two fundamental limitations.First,most of the existing schemes employ open-loop control,and thus are unable to track positional errors,resulting in failures in taking necessary online corrective actions.There are examples of a few works dealing with closed-loop electroencephalography(EEG)-based position control.These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule,which often creates a bottleneck preventing time-efficient control.Second,the existing brain-induced position controllers are designed to generate a position response like a traditional firstorder system,resulting in a large steady-state error.This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential(SSVEP)induced linkselection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors.Other than the above,the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors.Experiments undertaken reveal that the steady-state error is reduced to 0.2%.The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.展开更多
To address the problem of resonance in the control of a robot arm,a resonance suppression strategy is proposed for a single-joint humanoid robot arm based on the proportionalresonant(PR)controller.First,an arm joint m...To address the problem of resonance in the control of a robot arm,a resonance suppression strategy is proposed for a single-joint humanoid robot arm based on the proportionalresonant(PR)controller.First,an arm joint model of the humanoid robot is established.Then the influence of resonance frequency on the performance of the control system with the robot arm is analyzed.The voltage fluctuation of the drive motor caused by the changes in arm motion is recognized as the disturbance of the current loop.The PR controller has the characteristic of disturbance rejection at a specific frequency.The output fluctuation of the driving system caused by the change of arm motion state at the resonance frequency is suppressed.Therefore the output current of the inverter will not be affected by the vibration of the arm at the resonance frequency.Finally,the control system is verified by MATLAB/Simulink simulation.The simulation results demonstrate that the control strategy for the humanoid robot arm based on the PR controller can suppress the resonance of the arm effectively,improving the dynamic performance and system stability.展开更多
A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is establish...A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is established by projection pursuit evaluation based on indexes of humanoid robot arm motion in robotics and ergonomics field. Based on projection pursuit evaluation with timing information entropy and time degrees, a dynamic comprehensive evaluation method is proposed by linear weighting to each time's static model's indexes weight according to timing weighted vectors. Through comparing similarity comprehensive evaluation result based on static and dynamic comprehensive evaluation model, the results show that similarity based on dynamic comprehensive evaluation model is high. By comparing reliability, similarity and dispersion of static and dynamic comprehensive evaluation models, the results show that dynamic comprehensive evaluation result has better accuracy, stability and lower dispersion, and the result is more reasonable and real. Therefore, the dynamic comprehensive evaluation method proposed in this paper is more suitable for similarity comprehensive evaluation of humanoid robot arm motion.展开更多
This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each jo...This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each joint. To lighten the weight, almost all mechanical parts are made of aluminum and the robot control system is placed outside. The modular concept is adopted during the robot design process for time and cost saving. Considering the much greater torque acted on the two shoulder joints, the joint shells are strengthened in the design to increase joint stiffness and suppress system vibration. Meanwhile, to simplify the maintenance, a new spring pins electronic connector is designed to disassemble every joint, connector and link independently without cutting any cables. The teleoperation technology enables the robot to offer more convenient service definitely for people＇ s daily life. Virtual reality technology is used to solve the time delay problem during teleoperation. Finally, two typical daily chore experiments are implemented to prove the manipulation ability of the dexterous robot arm.展开更多
To address the problems of torque limit and controller saturation in the control of robot arm joint,an anti-windup control strategy is proposed for a humanoid robot arm,which is based on the integral state prediction ...To address the problems of torque limit and controller saturation in the control of robot arm joint,an anti-windup control strategy is proposed for a humanoid robot arm,which is based on the integral state prediction under the direct torque control system of brushless DC motor. First,the arm joint of the humanoid robot is modelled. Then the speed controller model and the influence of the initial value of the integral element on the system are analyzed. On the basis of the traditional antiwindup controller,an integral state estimator is set up. Under the condition of different load torques and the given speed,the integral steady-state value is estimated. Therefore the accumulation of the speed error terminates when the integrator reaches saturation. Then the predicted integral steady-state value is used as the initial value of the regulator to enter the linear region to make the system achieve the purpose of anti-windup. The simulation results demonstrate that the control strategy for the humanoid robot arm joint based on integral state prediction can play the role of anti-windup and suppress the overshoot of the system effectively. The system has a good dynamic performance.展开更多
To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output err...To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.展开更多
The main focus of this work was to design, develop and implementation of competitively robot arm with en- hanced control and stumpy cost. The robot arm was designed with four degrees of freedom and talented to accompl...The main focus of this work was to design, develop and implementation of competitively robot arm with en- hanced control and stumpy cost. The robot arm was designed with four degrees of freedom and talented to accomplish accurately simple tasks, such as light material handling, which will be integrated into a mobile platform that serves as an assistant for industrial workforce. The robot arm is equipped with several servo motors which do links between arms and perform arm movements. The servo motors include encoder so that no controller was implemented. To control the robot we used Labview, which performs inverse kinematic calculations and communicates the proper angles serially to a microcontroller that drives the servo motors with the capability of modifying position, speed and acceleration. Testing and validation of the robot arm was carried out and results shows that it work properly.展开更多
This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal t...This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal transduction, where synchronized neuronal firing induces coordinated muscle contractions that produce macroscopic movement. We implement a Chua circuit-driven robotic arm with tunable periodic/chaotic oscillations through parameter modulation and external current injection. Bifurcation analysis maps oscillation modes under varying external stimuli. Inductive coupling between two systems with distinct initial conditions facilitates magnetic energy transfer, optimized by an energy balance criterion. A bio-inspired exponential gain method dynamically regulates the coupling strength to optimize the energy transfer efficiency.The effects of ambient electromagnetic noise on synchronization are systematically quantified. The results indicate electrically modulatable robotic arm dynamics, with the coupled systems achieving autonomous rapid synchronization. Despite noise-induced desynchronization, inter-system errors rapidly decay and stabilize within bounded limits, confirming robust stability.展开更多
Reusable and flexible capturing of space debris is highly required in future aerospace technologies.A tendon-actuated flexible robotic arm is therefore proposed for capturing floating targets in this paper.Firstly,an ...Reusable and flexible capturing of space debris is highly required in future aerospace technologies.A tendon-actuated flexible robotic arm is therefore proposed for capturing floating targets in this paper.Firstly,an accurate dynamic model of the flexible robotic arm is established by using the absolute nodal coordinate formulation(ANCF)in the framework of the arbitrary Lagrangian-Eulerian(ALE)description and the natural coordinate formulation(NCF).The contact and self-contact dynamics of the flexible robotic arm when bending and grasping an object are considered via a fast contact detection approach.Then,the dynamic simulations of the flexible robotic arm for capturing floating targets are carried out to study the influence of the position,size,and mass of the target object on the grasping performance.Finally,a principle prototype of the tendon-actuated flexible robotic arm is manufactured to validate the dynamic model.The corresponding grasping experiments for objects of various shapes are also conducted to illustrate the excellent performance of the flexible robotic arm.展开更多
A hybrid control strategy integrating proportional derivative(PD)and the H-infinity control methodology is proposed for a serial two-link robotic manipulator with the goal of improving the tracking performance of the ...A hybrid control strategy integrating proportional derivative(PD)and the H-infinity control methodology is proposed for a serial two-link robotic manipulator with the goal of improving the tracking performance of the robot arm.The H-infinity controller has the ability to achieve a high performance and robustness in the presence of disturbances and uncertainties,while the PD controller is effective in stabilizing the manipulator.Simulation results using Matlab and Simulink show that the proposed hybrid controller,which integrates the advantages of both PD and H-infinity controllers,has the lowest rise time for the second link,the lowest settling time for the two links,the lowest peak time for both links,and the fastest decay of the error response.In addition,the hybrid control scheme also has the lowest mean square error value,with a 53.3%improvement over the H-infinity controller and a 91.8%improvement over the PD controller,indicating an improved trajectory tracking performance when compared with pure PD and pure H-infinity controllers,respectively.It was also found that the hybrid controller has the lowest integral absolute error,integral square error,integral time absolute error,and integral time square error for the second link,while the error values for the first link are satisfactory,showing a superior performance of the hybrid controller above the PD and H-infinity controllers,respectively.展开更多
An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,a...An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency.Second,a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to accelerate the search speed of the algorithm.Finally,the planning path is processed by pruning,removing redundant points and path smoothing fitting using cubic B-spline curves to improve the flexibility of the robotic arm.Through the six-axis robotic arm path planning simulation experiments on the MATLAB platform,the results show that the AGP-RRT∗algorithm reduces 87.34%in terms of the average running time and 40.39%in terms of the average path cost;Meanwhile,under two sets of complex environments A and B,the average running time of the AGP-RRT∗algorithm is shortened by 94.56%vs.95.37%,and the average path cost is reduced by 55.28%vs.47.82%,which proves the effectiveness of the AGP-RRT∗algorithm in improving the efficiency of multi-axis robotic arm path planning.展开更多
The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operationa...The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operational safety and efficiency. Existing path planning algorithms, while capable of delineating feasible trajectories, often fall short of achieving optimality, particularly concerning path length, search duration, and success likelihood. This study introduces an enhanced Rapidly-Exploring Random Tree (RRT) algorithm, meticulously designed to rectify the issues of node redundancy and the compromised path quality endemic to conventional RRT approaches. Through the integration of an adaptive pruning mechanism and a dynamic elliptical search strategy within the Informed RRT* framework, our algorithm efficiently refines the search tree by discarding branches that surpass the cost of the optimal path, thereby refining the search space and significantly boosting efficiency. Extensive comparative analysis across both two-dimensional and three-dimensional simulation settings underscores the algorithm’s proficiency in markedly improving path precision and search velocity, signifying a breakthrough in the domain of robotic arm path planning.展开更多
Inspired by the driving muscles of the human arm,a 4-Degree of Freedom(DOF)concentrated driving humanoid robotic arm is proposed based on a spatial double parallel four-bar mechanism.The four-bar mechanism design redu...Inspired by the driving muscles of the human arm,a 4-Degree of Freedom(DOF)concentrated driving humanoid robotic arm is proposed based on a spatial double parallel four-bar mechanism.The four-bar mechanism design reduces the inertia of the elbow-driving unit and the torque by 76.65%and 57.81%,respectively.Mimicking the human pose regulation strategy that the human arm picks up a heavy object by adjusting its posture naturally without complicated control,the robotic arm features an integrated position-level closed-form inverse solution method considering both geometric and load capacity limitations.This method consists of a geometric constraint model incorporating the arm angle(φ)and the Global Configuration(GC)to avoid joint limits and singularities,and a load capacity model to constrain the feasible domain of the arm angle.Further,trajectory tracking simulations and experiments are conducted to validate the feasibility of the proposed inverse solution method.The simulated maximum output torque,maximum output power and total energy consumption of the robotic arm are reduced by up to 2.0%,13.3%,and 33.3%,respectively.The experimental results demonstrate that the robotic arm can bear heavy loads in a human-like posture,effectively reducing the maximum output torque and energy consumption of the robotic arm by 1.83%and 5.03%,respectively,while avoiding joints beyond geometric and load capacity limitations.The proposed design provides a high payload–weight ratio and an efficient pose control solution for robotic arms,which can potentially broaden the application spectrum of humanoid robots.展开更多
Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment....Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment.With the aim to conveniently and accurately segment demonstration trajectories,a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model(BP-ARHMM)algorithm and generalised time warping(GTW)algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data.This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task.Then,it adopts the BP-AR-HMM algorithm to segment the demonstration trajectories,acquire the contained motion primitives,and establish the related task library.This segmentation approach is validated on the 6-degree-of-freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task.The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy.展开更多
The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual...The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.展开更多
This paper presents a firmware design and its implementation on a real time embedded system for driving a 4 DOF parallel robot arm.The firmware primarily comprised of two components to produce motion of the robot arm:...This paper presents a firmware design and its implementation on a real time embedded system for driving a 4 DOF parallel robot arm.The firmware primarily comprised of two components to produce motion of the robot arm:a)generation of continuous position coordinates and b)generation of actuating signals.These two componentswere processed in two different microcontrollerswith a common communication bus.The position generation algorithm produced and transmitted continuous position data to the motion generation algorithm in the form of G-code strings by reading the input positionswhichwere previously stored by the user in EEPROMmemory of the microcontroller.The receipt of a handshake signal synchronized the data transmission between these components through a communication bus.An LCD display and keypad were used as human-machine interface(HMI)to communicate with the user to set the robot target coordinates.The mechanical structure of the robot arm comprised of multiple links which were actuated by steppermotors.The workspace boundary were sensed by limit switches.The kinematic equations represented the gripper position for the corresponding input joint angles.A microcontroller was used to compute kinematic equations of the robot arm with the help of motion generation algorithm to generate actuation signals for the simultaneous movement of robot joints.The kinematic equations were solved with the dual-core capability of the microcontroller using real time operating system(RTOS),which made the computation faster with an average computation time of 198μs per step.The developed firmware was implemented and tested on a 4 DOF parallel manipulator using embedded microcontrollers for continuous pickup and place of the paper pot seedlings for automating the metering of pot seedlings.The cycle time taken for pickup and dropping of each seedling was 3.5 s with a success rate of 93.3%.展开更多
Developing robotic manipulators capable of performing effective physical interac- tion tasks is a challenging topic. In this study, we design a soft robotic arm （SRA） with multiple degrees of freedom inspired by the...Developing robotic manipulators capable of performing effective physical interac- tion tasks is a challenging topic. In this study, we design a soft robotic arm （SRA） with multiple degrees of freedom inspired by the flexible structures and the unique motion mechanism of the octopus arm. The SRA is fabricated with elastomeric materials, which consists of four series of integrated pneumatic chambers that play similar roles as the muscles in the octopus arm can achieve large bending in various directions with variable stiffness. This SRA displays specified movements via controlling pressure and selecting channels. Moreover, utilizing parallel control, the SRA demonstrates complicated three-dimensional motions. The force response and motion of the SRA are determined both experimentally and computationally. The applications of the present SRA include tightly coiling around the objects because of its large bending deformation （nearly 360°）, grasping multiple objects, and adjusting the grabbing mode in accordance with the shape of objects.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51305222)National Key Scientific and Technological Program of China(Grant No.2013ZX04001-021)
文摘Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.
文摘Brain-Computer interfacing(BCI)has currently added a new dimension in assistive robotics.Existing braincomputer interfaces designed for position control applications suffer from two fundamental limitations.First,most of the existing schemes employ open-loop control,and thus are unable to track positional errors,resulting in failures in taking necessary online corrective actions.There are examples of a few works dealing with closed-loop electroencephalography(EEG)-based position control.These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule,which often creates a bottleneck preventing time-efficient control.Second,the existing brain-induced position controllers are designed to generate a position response like a traditional firstorder system,resulting in a large steady-state error.This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential(SSVEP)induced linkselection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors.Other than the above,the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors.Experiments undertaken reveal that the steady-state error is reduced to 0.2%.The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.
基金Supported by the National Key Technology Research and Development Program of China(2018YFC1707104)National Natural Science Foundation of China(62076152)+1 种基金Natural Science Foundation of Shandong Province(ZR2017MF045)Beijing Advanced Innovation Center for Intelligent Robots and Systems。
文摘To address the problem of resonance in the control of a robot arm,a resonance suppression strategy is proposed for a single-joint humanoid robot arm based on the proportionalresonant(PR)controller.First,an arm joint model of the humanoid robot is established.Then the influence of resonance frequency on the performance of the control system with the robot arm is analyzed.The voltage fluctuation of the drive motor caused by the changes in arm motion is recognized as the disturbance of the current loop.The PR controller has the characteristic of disturbance rejection at a specific frequency.The output fluctuation of the driving system caused by the change of arm motion state at the resonance frequency is suppressed.Therefore the output current of the inverter will not be affected by the vibration of the arm at the resonance frequency.Finally,the control system is verified by MATLAB/Simulink simulation.The simulation results demonstrate that the control strategy for the humanoid robot arm based on the PR controller can suppress the resonance of the arm effectively,improving the dynamic performance and system stability.
基金Supported by the National Natural Science Foundation of China(51415016)
文摘A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is established by projection pursuit evaluation based on indexes of humanoid robot arm motion in robotics and ergonomics field. Based on projection pursuit evaluation with timing information entropy and time degrees, a dynamic comprehensive evaluation method is proposed by linear weighting to each time's static model's indexes weight according to timing weighted vectors. Through comparing similarity comprehensive evaluation result based on static and dynamic comprehensive evaluation model, the results show that similarity based on dynamic comprehensive evaluation model is high. By comparing reliability, similarity and dispersion of static and dynamic comprehensive evaluation models, the results show that dynamic comprehensive evaluation result has better accuracy, stability and lower dispersion, and the result is more reasonable and real. Therefore, the dynamic comprehensive evaluation method proposed in this paper is more suitable for similarity comprehensive evaluation of humanoid robot arm motion.
文摘This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each joint. To lighten the weight, almost all mechanical parts are made of aluminum and the robot control system is placed outside. The modular concept is adopted during the robot design process for time and cost saving. Considering the much greater torque acted on the two shoulder joints, the joint shells are strengthened in the design to increase joint stiffness and suppress system vibration. Meanwhile, to simplify the maintenance, a new spring pins electronic connector is designed to disassemble every joint, connector and link independently without cutting any cables. The teleoperation technology enables the robot to offer more convenient service definitely for people＇ s daily life. Virtual reality technology is used to solve the time delay problem during teleoperation. Finally, two typical daily chore experiments are implemented to prove the manipulation ability of the dexterous robot arm.
基金Supported by the National Natural Science Foundation of China(61175090,61703249)Shandong Provincial Natural Science Foundation,China(ZR2017MF045)
文摘To address the problems of torque limit and controller saturation in the control of robot arm joint,an anti-windup control strategy is proposed for a humanoid robot arm,which is based on the integral state prediction under the direct torque control system of brushless DC motor. First,the arm joint of the humanoid robot is modelled. Then the speed controller model and the influence of the initial value of the integral element on the system are analyzed. On the basis of the traditional antiwindup controller,an integral state estimator is set up. Under the condition of different load torques and the given speed,the integral steady-state value is estimated. Therefore the accumulation of the speed error terminates when the integrator reaches saturation. Then the predicted integral steady-state value is used as the initial value of the regulator to enter the linear region to make the system achieve the purpose of anti-windup. The simulation results demonstrate that the control strategy for the humanoid robot arm joint based on integral state prediction can play the role of anti-windup and suppress the overshoot of the system effectively. The system has a good dynamic performance.
文摘To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.
文摘The main focus of this work was to design, develop and implementation of competitively robot arm with en- hanced control and stumpy cost. The robot arm was designed with four degrees of freedom and talented to accomplish accurately simple tasks, such as light material handling, which will be integrated into a mobile platform that serves as an assistant for industrial workforce. The robot arm is equipped with several servo motors which do links between arms and perform arm movements. The servo motors include encoder so that no controller was implemented. To control the robot we used Labview, which performs inverse kinematic calculations and communicates the proper angles serially to a microcontroller that drives the servo motors with the capability of modifying position, speed and acceleration. Testing and validation of the robot arm was carried out and results shows that it work properly.
基金Project supported by the National Key R&D Program of China (Grant No. 2023YFD2000601-02)。
文摘This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal transduction, where synchronized neuronal firing induces coordinated muscle contractions that produce macroscopic movement. We implement a Chua circuit-driven robotic arm with tunable periodic/chaotic oscillations through parameter modulation and external current injection. Bifurcation analysis maps oscillation modes under varying external stimuli. Inductive coupling between two systems with distinct initial conditions facilitates magnetic energy transfer, optimized by an energy balance criterion. A bio-inspired exponential gain method dynamically regulates the coupling strength to optimize the energy transfer efficiency.The effects of ambient electromagnetic noise on synchronization are systematically quantified. The results indicate electrically modulatable robotic arm dynamics, with the coupled systems achieving autonomous rapid synchronization. Despite noise-induced desynchronization, inter-system errors rapidly decay and stabilize within bounded limits, confirming robust stability.
基金funded by the"14th Five-Year Plan"Civil Aerospace Pre-research Project of China(Grant No.D010301).
文摘Reusable and flexible capturing of space debris is highly required in future aerospace technologies.A tendon-actuated flexible robotic arm is therefore proposed for capturing floating targets in this paper.Firstly,an accurate dynamic model of the flexible robotic arm is established by using the absolute nodal coordinate formulation(ANCF)in the framework of the arbitrary Lagrangian-Eulerian(ALE)description and the natural coordinate formulation(NCF).The contact and self-contact dynamics of the flexible robotic arm when bending and grasping an object are considered via a fast contact detection approach.Then,the dynamic simulations of the flexible robotic arm for capturing floating targets are carried out to study the influence of the position,size,and mass of the target object on the grasping performance.Finally,a principle prototype of the tendon-actuated flexible robotic arm is manufactured to validate the dynamic model.The corresponding grasping experiments for objects of various shapes are also conducted to illustrate the excellent performance of the flexible robotic arm.
文摘A hybrid control strategy integrating proportional derivative(PD)and the H-infinity control methodology is proposed for a serial two-link robotic manipulator with the goal of improving the tracking performance of the robot arm.The H-infinity controller has the ability to achieve a high performance and robustness in the presence of disturbances and uncertainties,while the PD controller is effective in stabilizing the manipulator.Simulation results using Matlab and Simulink show that the proposed hybrid controller,which integrates the advantages of both PD and H-infinity controllers,has the lowest rise time for the second link,the lowest settling time for the two links,the lowest peak time for both links,and the fastest decay of the error response.In addition,the hybrid control scheme also has the lowest mean square error value,with a 53.3%improvement over the H-infinity controller and a 91.8%improvement over the PD controller,indicating an improved trajectory tracking performance when compared with pure PD and pure H-infinity controllers,respectively.It was also found that the hybrid controller has the lowest integral absolute error,integral square error,integral time absolute error,and integral time square error for the second link,while the error values for the first link are satisfactory,showing a superior performance of the hybrid controller above the PD and H-infinity controllers,respectively.
基金supported by Foundation of key Laboratory of AI and Information Processing of Education Department of Guangxi(No.2022GXZDSY002)(Hechi University),Foundation of Guangxi Key Laboratory of Automobile Components and Vehicle Technology(Nos.2022GKLACVTKF04,2023GKLACVTZZ06)。
文摘An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency.Second,a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to accelerate the search speed of the algorithm.Finally,the planning path is processed by pruning,removing redundant points and path smoothing fitting using cubic B-spline curves to improve the flexibility of the robotic arm.Through the six-axis robotic arm path planning simulation experiments on the MATLAB platform,the results show that the AGP-RRT∗algorithm reduces 87.34%in terms of the average running time and 40.39%in terms of the average path cost;Meanwhile,under two sets of complex environments A and B,the average running time of the AGP-RRT∗algorithm is shortened by 94.56%vs.95.37%,and the average path cost is reduced by 55.28%vs.47.82%,which proves the effectiveness of the AGP-RRT∗algorithm in improving the efficiency of multi-axis robotic arm path planning.
文摘The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operational safety and efficiency. Existing path planning algorithms, while capable of delineating feasible trajectories, often fall short of achieving optimality, particularly concerning path length, search duration, and success likelihood. This study introduces an enhanced Rapidly-Exploring Random Tree (RRT) algorithm, meticulously designed to rectify the issues of node redundancy and the compromised path quality endemic to conventional RRT approaches. Through the integration of an adaptive pruning mechanism and a dynamic elliptical search strategy within the Informed RRT* framework, our algorithm efficiently refines the search tree by discarding branches that surpass the cost of the optimal path, thereby refining the search space and significantly boosting efficiency. Extensive comparative analysis across both two-dimensional and three-dimensional simulation settings underscores the algorithm’s proficiency in markedly improving path precision and search velocity, signifying a breakthrough in the domain of robotic arm path planning.
基金funded by the National Natural Science Foundation of China(NO.52175069).
文摘Inspired by the driving muscles of the human arm,a 4-Degree of Freedom(DOF)concentrated driving humanoid robotic arm is proposed based on a spatial double parallel four-bar mechanism.The four-bar mechanism design reduces the inertia of the elbow-driving unit and the torque by 76.65%and 57.81%,respectively.Mimicking the human pose regulation strategy that the human arm picks up a heavy object by adjusting its posture naturally without complicated control,the robotic arm features an integrated position-level closed-form inverse solution method considering both geometric and load capacity limitations.This method consists of a geometric constraint model incorporating the arm angle(φ)and the Global Configuration(GC)to avoid joint limits and singularities,and a load capacity model to constrain the feasible domain of the arm angle.Further,trajectory tracking simulations and experiments are conducted to validate the feasibility of the proposed inverse solution method.The simulated maximum output torque,maximum output power and total energy consumption of the robotic arm are reduced by up to 2.0%,13.3%,and 33.3%,respectively.The experimental results demonstrate that the robotic arm can bear heavy loads in a human-like posture,effectively reducing the maximum output torque and energy consumption of the robotic arm by 1.83%and 5.03%,respectively,while avoiding joints beyond geometric and load capacity limitations.The proposed design provides a high payload–weight ratio and an efficient pose control solution for robotic arms,which can potentially broaden the application spectrum of humanoid robots.
基金Doctoral Research Start-up Fund of Shandong Jiaotong University,Grant/Award Number:BS2024009Natural Science Foundation of Shandong Province of China,Grant/Award Number:ZR2022ME087+1 种基金State Key Laboratory of Robotics and Systems(HIT),Grant/Award Number:SKLRS-2024-KF-09Open Access Publication Fund of Universität Hamburg。
文摘Segmentation of demonstration trajectories and learning the contained motion primitives can effectively enhance the assistive robot's intelligence to flexibly reproduce learnt tasks in an unstructured environment.With the aim to conveniently and accurately segment demonstration trajectories,a novel demonstration trajectory segmentation approach is proposed based on the beta process autoregressive hidden Markov model(BP-ARHMM)algorithm and generalised time warping(GTW)algorithm aiming to enhance the segmentation accuracy utilising acquired demonstration data.This approach first adopts the GTW algorithm to align the multiple demonstration trajectories for the same task.Then,it adopts the BP-AR-HMM algorithm to segment the demonstration trajectories,acquire the contained motion primitives,and establish the related task library.This segmentation approach is validated on the 6-degree-of-freedom JACO robotic arm by assisting users to accomplish a holding water glass task and an eating task.The experimental results show that the motion primitives within the trajectories can be correctly segmented with a high segmentation accuracy.
基金supported by UGC Sponsored UPE-ⅡProject in Cognitive Science of Jadavpur University,Kolkata
文摘The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.
文摘This paper presents a firmware design and its implementation on a real time embedded system for driving a 4 DOF parallel robot arm.The firmware primarily comprised of two components to produce motion of the robot arm:a)generation of continuous position coordinates and b)generation of actuating signals.These two componentswere processed in two different microcontrollerswith a common communication bus.The position generation algorithm produced and transmitted continuous position data to the motion generation algorithm in the form of G-code strings by reading the input positionswhichwere previously stored by the user in EEPROMmemory of the microcontroller.The receipt of a handshake signal synchronized the data transmission between these components through a communication bus.An LCD display and keypad were used as human-machine interface(HMI)to communicate with the user to set the robot target coordinates.The mechanical structure of the robot arm comprised of multiple links which were actuated by steppermotors.The workspace boundary were sensed by limit switches.The kinematic equations represented the gripper position for the corresponding input joint angles.A microcontroller was used to compute kinematic equations of the robot arm with the help of motion generation algorithm to generate actuation signals for the simultaneous movement of robot joints.The kinematic equations were solved with the dual-core capability of the microcontroller using real time operating system(RTOS),which made the computation faster with an average computation time of 198μs per step.The developed firmware was implemented and tested on a 4 DOF parallel manipulator using embedded microcontrollers for continuous pickup and place of the paper pot seedlings for automating the metering of pot seedlings.The cycle time taken for pickup and dropping of each seedling was 3.5 s with a success rate of 93.3%.
基金This work is supported by the National Natural Science Foundation of China （nos. 11525210, 11621062, and 91748209） and the Fundamental Research Funds for the Central Universities.
文摘Developing robotic manipulators capable of performing effective physical interac- tion tasks is a challenging topic. In this study, we design a soft robotic arm （SRA） with multiple degrees of freedom inspired by the flexible structures and the unique motion mechanism of the octopus arm. The SRA is fabricated with elastomeric materials, which consists of four series of integrated pneumatic chambers that play similar roles as the muscles in the octopus arm can achieve large bending in various directions with variable stiffness. This SRA displays specified movements via controlling pressure and selecting channels. Moreover, utilizing parallel control, the SRA demonstrates complicated three-dimensional motions. The force response and motion of the SRA are determined both experimentally and computationally. The applications of the present SRA include tightly coiling around the objects because of its large bending deformation （nearly 360°）, grasping multiple objects, and adjusting the grabbing mode in accordance with the shape of objects.
